Gravitational Search Algorithm for Assembly Sequence Planning
Assembly sequence planning (ASP) refers to the process of arrangement of a particular assembly sequence with regard to a product design. In assembly sequence planning, the relationships between components such as the geometry of compliant assemblies should be taken into account before a precedence d...
| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/9784/ http://umpir.ump.edu.my/id/eprint/9784/1/Gravitational%20Search%20Algorithm%20for%20Assembly%20Sequence%20Planning.pdf http://umpir.ump.edu.my/id/eprint/9784/7/Gravitational%20Search%20Algorithm%20for%20Assembly%20Sequence%20Planning%20-%20Abstract.pdf |
| Summary: | Assembly sequence planning (ASP) refers to the process of arrangement of a particular assembly sequence with regard to a product design. In assembly sequence planning, the relationships between components such as the geometry of compliant assemblies should be taken into account before a precedence diagram is eventually built and feasible assembly sequences can be generated. A better assembly sequence can contribute to reduce the cost and time of the manufacturing process, that is, among NP-hard problems. Thus, it is needed to find the optimal sequence from the feasible assembly sequences. In past few years, many optimization techniques have been used to solve the assembly sequence planning problem include Simulated Annealing (SA), Genetic Algorithm (GA), and binary Particle Swarm Optimization (BPSO). In this paper, an approach using Gravitational Search Algorithm (GSA) which is a heuristic optimization algorithm that incorporates the Newton’s law of gravity and the law of motion into analytical studies of systems is proposed to solve the assembly sequence planning problem. The experimental results show that the proposed approach is more efficient in solving the assembly sequence planning problem, with less of total assembly time in comparison with the three other approaches. |
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